----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  D:\Vicard\VV\re\inprogress\BRV\results\prediction1_reconstr_fe.log
  log type:  text
 opened on:  29 Sep 2017, 23:34:04

. 
. use $Output\dataset_brv_fe_reconstr, clear

. global condition  "entry_ele!=1994 & entry_ele!=1995"

. 
. foreach def in ele1 {
  2. 
.         foreach var in diff {
  3. 
.                 eststo: reg dprior `var' age_`def'                              if $condition, r cluster(i)
  4.                 eststo: reg dprior `var' age_`def' `var'_`def'  if $condition, r cluster(i)
  5.                 eststo: reg dprior `var' age_`def' `var'_`def'  if $condition, vce(bootstrap) 
  6.                 eststo: reg dprior `var'_`def'_* `def'_*            if $condition, r cluster(i)
  7.                 *eststo: reg dprior `var'_`def'_* `def'_*           if $condition, vce(bootstrap) 
.                 drop `var'_`def'_9      `def'_9 
  8.                 eststo: reg dprior `var' `var'_`def'_* `def'_*     if $condition, r cluster(i)
  9.                 *eststo: reg dprior `var' `var'_`def'_* `def'_*            if $condition, vce(bootstrap) 
.                 
.                 set linesize 250
 10.                 esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) compress r2 starlevels(c 0.1 b 0.05 a 0.01)  se 
 11.                 esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) r2  starlevels({$^c$} 0.1 {$^b$} 0.05 {$^a$} 0.01) se tex label  title() 
 12.                 eststo clear
 13.         }
 14. }

Linear regression                               Number of obs     =  1,495,774
                                                F(2, 40758)       =    2021.32
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0351
                                                Root MSE          =     1.1781

                                 (Std. Err. adjusted for 40,759 clusters in i)
------------------------------------------------------------------------------
             |               Robust
      dprior |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        diff |   .0674331   .0010899    61.87   0.000     .0652968    .0695694
    age_ele1 |  -.0096185   .0006966   -13.81   0.000    -.0109838   -.0082532
       _cons |   .0169489   .0026774     6.33   0.000     .0117012    .0221967
------------------------------------------------------------------------------
(est1 stored)

Linear regression                               Number of obs     =  1,495,774
                                                F(3, 40758)       =    1534.46
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0353
                                                Root MSE          =      1.178

                                 (Std. Err. adjusted for 40,759 clusters in i)
------------------------------------------------------------------------------
             |               Robust
      dprior |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        diff |   .0779847   .0014501    53.78   0.000     .0751425    .0808269
    age_ele1 |  -.0099472    .000688   -14.46   0.000    -.0112958   -.0085987
   diff_ele1 |  -.0032481   .0003753    -8.65   0.000    -.0039837   -.0025124
       _cons |   .0177689   .0026637     6.67   0.000      .012548    .0229898
------------------------------------------------------------------------------
(est2 stored)
(running regress on estimation sample)

Bootstrap replications (50)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50

Linear regression                               Number of obs     =  1,495,774
                                                Replications      =         50
                                                Wald chi2(3)      =   18223.28
                                                Prob > chi2       =     0.0000
                                                R-squared         =     0.0353
                                                Adj R-squared     =     0.0353
                                                Root MSE          =     1.1780

------------------------------------------------------------------------------
             |   Observed   Bootstrap                         Normal-based
      dprior |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        diff |   .0779847   .0009472    82.33   0.000     .0761282    .0798412
    age_ele1 |  -.0099472   .0006011   -16.55   0.000    -.0111254    -.008769
   diff_ele1 |  -.0032481   .0002254   -14.41   0.000    -.0036899   -.0028062
       _cons |   .0177689   .0024988     7.11   0.000     .0128714    .0226664
------------------------------------------------------------------------------
(est3 stored)
note: diff_ele1_1 omitted because of collinearity
note: ele1_1 omitted because of collinearity
note: ele1_9 omitted because of collinearity

Linear regression                               Number of obs     =  1,495,774
                                                F(15, 40758)      =     320.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0354
                                                Root MSE          =      1.178

                                 (Std. Err. adjusted for 40,759 clusters in i)
------------------------------------------------------------------------------
             |               Robust
      dprior |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 diff_ele1_1 |          0  (omitted)
 diff_ele1_2 |   .0723449   .0011263    64.23   0.000     .0701373    .0745525
 diff_ele1_3 |   .0662838   .0013297    49.85   0.000     .0636775    .0688901
 diff_ele1_4 |    .066484   .0017462    38.07   0.000     .0630615    .0699066
 diff_ele1_5 |   .0577428   .0018333    31.50   0.000     .0541495    .0613361
 diff_ele1_6 |   .0605664   .0024348    24.88   0.000     .0557942    .0653385
 diff_ele1_7 |   .0542242   .0023998    22.60   0.000     .0495205    .0589279
 diff_ele1_8 |   .0557013   .0037959    14.67   0.000     .0482613    .0631413
 diff_ele1_9 |   .0559289    .004799    11.65   0.000     .0465227    .0653351
      ele1_1 |          0  (omitted)
      ele1_2 |   .0481502   .0109181     4.41   0.000     .0267506    .0695499
      ele1_3 |   .0507993   .0110725     4.59   0.000      .029097    .0725016
      ele1_4 |   .0258128   .0110163     2.34   0.019     .0042205     .047405
      ele1_5 |   .0050578   .0111612     0.45   0.650    -.0168185    .0269341
      ele1_6 |   .0056276   .0117256     0.48   0.631    -.0173548      .02861
      ele1_7 |   .0078064     .01184     0.66   0.510    -.0154002     .031013
      ele1_8 |   .0039324   .0130935     0.30   0.764    -.0217312     .029596
      ele1_9 |          0  (omitted)
       _cons |   -.052343   .0108855    -4.81   0.000    -.0736787   -.0310073
------------------------------------------------------------------------------
(est4 stored)
note: diff_ele1_1 omitted because of collinearity
note: ele1_1 omitted because of collinearity

Linear regression                               Number of obs     =  1,495,774
                                                F(15, 40758)      =     320.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0354
                                                Root MSE          =      1.178

                                 (Std. Err. adjusted for 40,759 clusters in i)
------------------------------------------------------------------------------
             |               Robust
      dprior |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        diff |   .0559289    .004799    11.65   0.000     .0465227    .0653351
 diff_ele1_1 |          0  (omitted)
 diff_ele1_2 |    .016416    .004725     3.47   0.001     .0071549    .0256771
 diff_ele1_3 |   .0103549   .0046363     2.23   0.026     .0012677    .0194421
 diff_ele1_4 |   .0105551   .0047187     2.24   0.025     .0013063    .0198039
 diff_ele1_5 |   .0018139   .0044951     0.40   0.687    -.0069966    .0106245
 diff_ele1_6 |   .0046375   .0049724     0.93   0.351    -.0051086    .0143836
 diff_ele1_7 |  -.0017047   .0048294    -0.35   0.724    -.0111704    .0077611
 diff_ele1_8 |  -.0002276   .0046603    -0.05   0.961    -.0093619    .0089066
      ele1_1 |          0  (omitted)
      ele1_2 |   .0481502   .0109181     4.41   0.000     .0267506    .0695499
      ele1_3 |   .0507993   .0110725     4.59   0.000      .029097    .0725016
      ele1_4 |   .0258128   .0110163     2.34   0.019     .0042205     .047405
      ele1_5 |   .0050578   .0111612     0.45   0.650    -.0168185    .0269341
      ele1_6 |   .0056276   .0117256     0.48   0.631    -.0173548      .02861
      ele1_7 |   .0078064     .01184     0.66   0.510    -.0154002     .031013
      ele1_8 |   .0039324   .0130935     0.30   0.764    -.0217312     .029596
       _cons |   -.052343   .0108855    -4.81   0.000    -.0736787   -.0310073
------------------------------------------------------------------------------
(est5 stored)

-----------------------------------------------------------------
                 (1)        (2)        (3)        (4)        (5) 
                est1       est2       est3       est4       est5 
-----------------------------------------------------------------
diff           0.067a     0.078a     0.078a                0.056a
             (0.001)    (0.001)    (0.001)               (0.005) 

age_ele1      -0.010a    -0.010a    -0.010a                      
             (0.001)    (0.001)    (0.001)                       

diff_ele1                -0.003a    -0.003a                      
                        (0.000)    (0.000)                       

diff_el~_1                                      0.000      0.000 
                                                  (.)        (.) 

diff_ele~2                                      0.072a     0.016a
                                              (0.001)    (0.005) 

diff_ele~3                                      0.066a     0.010b
                                              (0.001)    (0.005) 

diff_ele~4                                      0.066a     0.011b
                                              (0.002)    (0.005) 

diff_ele~5                                      0.058a     0.002 
                                              (0.002)    (0.004) 

diff_ele~6                                      0.061a     0.005 
                                              (0.002)    (0.005) 

diff_ele~7                                      0.054a    -0.002 
                                              (0.002)    (0.005) 

diff_ele~8                                      0.056a    -0.000 
                                              (0.004)    (0.005) 

diff_ele~9                                      0.056a           
                                              (0.005)            

ele1_1                                          0.000      0.000 
                                                  (.)        (.) 

ele1_2                                          0.048a     0.048a
                                              (0.011)    (0.011) 

ele1_3                                          0.051a     0.051a
                                              (0.011)    (0.011) 

ele1_4                                          0.026b     0.026b
                                              (0.011)    (0.011) 

ele1_5                                          0.005      0.005 
                                              (0.011)    (0.011) 

ele1_6                                          0.006      0.006 
                                              (0.012)    (0.012) 

ele1_7                                          0.008      0.008 
                                              (0.012)    (0.012) 

ele1_8                                          0.004      0.004 
                                              (0.013)    (0.013) 

ele1_9                                          0.000            
                                                  (.)            
-----------------------------------------------------------------
N            1495774    1495774    1495774    1495774    1495774 
R-sq           0.035      0.035      0.035      0.035      0.035 
-----------------------------------------------------------------
Standard errors in parentheses
c p<0.1, b p<0.05, a p<0.01

{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{5}{c}}
\hline\hline
                    &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}\\
                    &\multicolumn{1}{c}{est1}&\multicolumn{1}{c}{est2}&\multicolumn{1}{c}{est3}&\multicolumn{1}{c}{est4}&\multicolumn{1}{c}{est5}\\
\hline
$\widehat{a}\_{ijkt}-\varepsilon^q\_{ijk,t-1}$&       0.067{$^a$}&       0.078{$^a$}&       0.078{$^a$}&                  &       0.056{$^a$}\\
                    &     (0.001)      &     (0.001)      &     (0.001)      &                  &     (0.005)      \\
[1em]
Age$ \_{ijkt}$       &      -0.010{$^a$}&      -0.010{$^a$}&      -0.010{$^a$}&                  &                  \\
                    &     (0.001)      &     (0.001)      &     (0.001)      &                  &                  \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}$&                  &      -0.003{$^a$}&      -0.003{$^a$}&                  &                  \\
                    &                  &     (0.000)      &     (0.000)      &                  &                  \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=1$&                  &                  &                  &       0.000      &       0.000      \\
                    &                  &                  &                  &         (.)      &         (.)      \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=2$&                  &                  &                  &       0.072{$^a$}&       0.016{$^a$}\\
                    &                  &                  &                  &     (0.001)      &     (0.005)      \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=3$&                  &                  &                  &       0.066{$^a$}&       0.010{$^b$}\\
                    &                  &                  &                  &     (0.001)      &     (0.005)      \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=4$&                  &                  &                  &       0.066{$^a$}&       0.011{$^b$}\\
                    &                  &                  &                  &     (0.002)      &     (0.005)      \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=5$&                  &                  &                  &       0.058{$^a$}&       0.002      \\
                    &                  &                  &                  &     (0.002)      &     (0.004)      \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=6$&                  &                  &                  &       0.061{$^a$}&       0.005      \\
                    &                  &                  &                  &     (0.002)      &     (0.005)      \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=7$&                  &                  &                  &       0.054{$^a$}&      -0.002      \\
                    &                  &                  &                  &     (0.002)      &     (0.005)      \\
[1em]
\hspace{1cm} $\times$ Age$ \_{ijkt}=8$&                  &                  &                  &       0.056{$^a$}&      -0.000      \\
                    &                  &                  &                  &     (0.004)      &     (0.005)      \\
[1em]
diff\_ele1\_9         &                  &                  &                  &       0.056{$^a$}&                  \\
                    &                  &                  &                  &     (0.005)      &                  \\
[1em]
age\_ele110==     1.0000&                  &                  &                  &       0.000      &       0.000      \\
                    &                  &                  &                  &         (.)      &         (.)      \\
[1em]
age\_ele110==     2.0000&                  &                  &                  &       0.048{$^a$}&       0.048{$^a$}\\
                    &                  &                  &                  &     (0.011)      &     (0.011)      \\
[1em]
age\_ele110==     3.0000&                  &                  &                  &       0.051{$^a$}&       0.051{$^a$}\\
                    &                  &                  &                  &     (0.011)      &     (0.011)      \\
[1em]
age\_ele110==     4.0000&                  &                  &                  &       0.026{$^b$}&       0.026{$^b$}\\
                    &                  &                  &                  &     (0.011)      &     (0.011)      \\
[1em]
age\_ele110==     5.0000&                  &                  &                  &       0.005      &       0.005      \\
                    &                  &                  &                  &     (0.011)      &     (0.011)      \\
[1em]
age\_ele110==     6.0000&                  &                  &                  &       0.006      &       0.006      \\
                    &                  &                  &                  &     (0.012)      &     (0.012)      \\
[1em]
age\_ele110==     7.0000&                  &                  &                  &       0.008      &       0.008      \\
                    &                  &                  &                  &     (0.012)      &     (0.012)      \\
[1em]
age\_ele110==     8.0000&                  &                  &                  &       0.004      &       0.004      \\
                    &                  &                  &                  &     (0.013)      &     (0.013)      \\
[1em]
ele1\_9              &                  &                  &                  &       0.000      &                  \\
                    &                  &                  &                  &         (.)      &                  \\
\hline
Observations        &     1495774      &     1495774      &     1495774      &     1495774      &     1495774      \\
\(R^{2}\)           &       0.035      &       0.035      &       0.035      &       0.035      &       0.035      \\
\hline\hline
\multicolumn{6}{l}{\footnotesize Standard errors in parentheses}\\
\multicolumn{6}{l}{\footnotesize {$^c$} p<0.1, {$^b$} p<0.05, {$^a$} p<0.01}\\
\end{tabular}
}

. 
. 
. 
. ***************************************************************************
. * F - Level :  qty and UV for main definition of experience, no jkt in prices *
. ***************************************************************************
. 
. foreach res in "res_fe" {
  2.         foreach age in "age_ele1" {
  3.         *
.         use $Output\dataset_brv_fe_reconstr, clear
  4.         tab `age', gen(aged)
  5.         replace aged10 = 1 if `age'>=10
  6.         drop aged11
  7.         tab year, gen(yeard)
  8.         *
.         gen size_l1     = log(quantity_l1/quantity_tot_l1)
  9.         *
.         *label var `res'      "Demand shock"
.         *
.         global condition     "entry_ele!=1994 & entry_ele!=1995 "
 10.         *
.         sort ijk year
 11.         *
.         label var `age'         "Age$ _{ijkt}$" 
 12.         label var aged1         "Age$ _{ijkt}=1$" 
 13.         label var aged2         "Age$ _{ijkt}=2$" 
 14.         label var aged3         "Age$ _{ijkt}=3$" 
 15.         label var aged4         "Age$ _{ijkt}=4$" 
 16.         label var aged5         "Age$ _{ijkt}=5$" 
 17.         label var aged6         "Age$ _{ijkt}=6$" 
 18.         label var aged7         "Age$ _{ijkt}=7$" 
 19.         label var aged8         "Age$ _{ijkt}=8$" 
 20.         label var aged9         "Age$ _{ijkt}=9$" 
 21.         *label var aged10       "Age$ _{ijkt}=10$" 
.         *
.         eststo: reg `res'_qty                   `age'           if $condition, ro cluster(i) 
 22.         eststo: reg `res'_qty                   aged2-aged9     if $condition, ro cluster(i) 
 23.         test aged3 = aged4
 24.         test aged3 = aged5
 25.         test aged3 = aged6
 26.         test aged3 = aged7
 27.         test aged4 = aged5
 28.         test aged4 = aged6
 29.         test aged4 = aged7
 30.         test aged5 = aged6
 31.         test aged5 = aged7
 32.         test aged6 = aged7
 33. 
.         eststo: areg `res'_qty          aged2-aged9     if $condition , a(ijk) cluster(i)
 34.         eststo: reg `res'_uv_nojkt  `age'               if $condition  & e(sample), ro cluster(i)
 35.         eststo: reg `res'_uv_nojkt      aged2-aged9     if $condition  & e(sample), ro cluster(i)
 36.         eststo: areg `res'_uv_nojkt aged2-aged9     if $condition  & e(sample), a(ijk) cluster(i)
 37.         /* including size (t-1) as control */
.         eststo: reg `res'_uv_nojkt aged3-aged9 size_l1      if $condition & e(sample), cluster(i)
 38.         eststo: areg `res'_uv_nojkt aged3-aged9 size_l1 if $condition & e(sample), a(ijk) cluster(i)
 39.         set linesize 250
 40.         esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) compress r2 starlevels(c 0.1 b 0.05 a 0.01)  se 
 41.         esttab, mtitles drop(_cons) b(%5.3f) se(%5.3f) r2  starlevels({$^c$} 0.1 {$^b$} 0.05 {$^a$} 0.01) se tex label  title() 
 42.         eststo clear
 43.         }
 44. }

       Age$ |
   _{ijkt}$ |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |  2,449,103       39.30       39.30
          2 |    968,634       15.54       54.84
          3 |    785,088       12.60       67.44
          4 |    553,911        8.89       76.33
          5 |    407,470        6.54       82.87
          6 |    309,304        4.96       87.83
          7 |    236,884        3.80       91.63
          8 |    184,139        2.95       94.59
          9 |    143,144        2.30       96.88
         10 |    111,344        1.79       98.67
         11 |     82,823        1.33      100.00
------------+-----------------------------------
      Total |  6,231,844      100.00
(962,510 real changes made)

       Year |      Freq.     Percent        Cum.
------------+-----------------------------------
       1996 |    689,343        9.69        9.69
       1997 |    755,574       10.62       20.32
       1998 |    773,410       10.88       31.19
       1999 |    789,051       11.10       42.29
       2000 |    813,596       11.44       53.73
       2001 |    814,532       11.45       65.18
       2002 |    824,643       11.60       76.78
       2003 |    815,042       11.46       88.24
       2004 |    836,340       11.76      100.00
------------+-----------------------------------
      Total |  7,111,531      100.00
(3,885,957 missing values generated)

Linear regression                               Number of obs     =  3,741,140
                                                F(1, 72493)       =    5404.57
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0118
                                                Root MSE          =     1.2463

                                 (Std. Err. adjusted for 72,494 clusters in i)
------------------------------------------------------------------------------
             |               Robust
  res_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |   .0852723   .0011599    73.52   0.000     .0829989    .0875457
       _cons |   -.262149   .0033038   -79.35   0.000    -.2686244   -.2556736
------------------------------------------------------------------------------
(est1 stored)

Linear regression                               Number of obs     =  3,741,140
                                                F(8, 72493)       =     810.43
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0123
                                                Root MSE          =     1.2459

                                 (Std. Err. adjusted for 72,494 clusters in i)
------------------------------------------------------------------------------
             |               Robust
  res_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged2 |   .1094932   .0022893    47.83   0.000     .1050062    .1139802
       aged3 |    .228521   .0036742    62.20   0.000     .2213196    .2357225
       aged4 |   .3115576   .0042395    73.49   0.000     .3032481    .3198671
       aged5 |   .3643719   .0052088    69.95   0.000     .3541627    .3745812
       aged6 |   .4185863   .0067549    61.97   0.000     .4053468    .4318259
       aged7 |   .4614937   .0085549    53.95   0.000     .4447262    .4782613
       aged8 |   .4905618   .0109562    44.77   0.000     .4690876     .512036
       aged9 |   .5146017   .0164741    31.24   0.000     .4823126    .5468908
       _cons |  -.1889959   .0027526   -68.66   0.000    -.1943911   -.1836008
------------------------------------------------------------------------------
(est2 stored)

 ( 1)  aged3 - aged4 = 0

       F(  1, 72493) =  807.12
            Prob > F =    0.0000

 ( 1)  aged3 - aged5 = 0

       F(  1, 72493) =  895.96
            Prob > F =    0.0000

 ( 1)  aged3 - aged6 = 0

       F(  1, 72493) =  906.21
            Prob > F =    0.0000

 ( 1)  aged3 - aged7 = 0

       F(  1, 72493) =  818.99
            Prob > F =    0.0000

 ( 1)  aged4 - aged5 = 0

       F(  1, 72493) =  207.49
            Prob > F =    0.0000

 ( 1)  aged4 - aged6 = 0

       F(  1, 72493) =  371.41
            Prob > F =    0.0000

 ( 1)  aged4 - aged7 = 0

       F(  1, 72493) =  391.48
            Prob > F =    0.0000

 ( 1)  aged5 - aged6 = 0

       F(  1, 72493) =  123.55
            Prob > F =    0.0000

 ( 1)  aged5 - aged7 = 0

       F(  1, 72493) =  183.98
            Prob > F =    0.0000

 ( 1)  aged6 - aged7 = 0

       F(  1, 72493) =   51.86
            Prob > F =    0.0000

Linear regression, absorbing indicators         Number of obs     =  3,741,140
                                                F(   8,  72493)   =      37.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.7097
                                                Adj R-squared     =     0.4150
                                                Root MSE          =     0.9589

                                 (Std. Err. adjusted for 72,494 clusters in i)
------------------------------------------------------------------------------
             |               Robust
  res_fe_qty |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged2 |   .0251543   .0029375     8.56   0.000     .0193969    .0309117
       aged3 |   .0672188   .0045321    14.83   0.000     .0583359    .0761016
       aged4 |   .0872917   .0055805    15.64   0.000     .0763539    .0982296
       aged5 |   .0893091   .0074046    12.06   0.000      .074796    .1038222
       aged6 |   .0879418   .0094794     9.28   0.000     .0693621    .1065214
       aged7 |   .0870325   .0115923     7.51   0.000     .0643117    .1097533
       aged8 |   .0793243   .0143714     5.52   0.000     .0511564    .1074923
       aged9 |   .0802836   .0192948     4.16   0.000     .0424659    .1181012
       _cons |  -.1130558   .0017882   -63.22   0.000    -.1165606    -.109551
-------------+----------------------------------------------------------------
         ijk |   absorbed                                 (1884495 categories)
(est3 stored)

Linear regression                               Number of obs     =  3,741,140
                                                F(1, 72493)       =     337.67
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0008
                                                Root MSE          =     .67991

                                 (Std. Err. adjusted for 72,494 clusters in i)
------------------------------------------------------------------------------
             |               Robust
res_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    age_ele1 |  -.0117063    .000637   -18.38   0.000     -.012955   -.0104577
       _cons |   .0315011   .0015444    20.40   0.000      .028474    .0345282
------------------------------------------------------------------------------
(est4 stored)

Linear regression                               Number of obs     =  3,741,140
                                                F(8, 72493)       =      61.91
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0008
                                                Root MSE          =     .67988

                                 (Std. Err. adjusted for 72,494 clusters in i)
------------------------------------------------------------------------------
             |               Robust
res_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged2 |  -.0221599   .0012036   -18.41   0.000     -.024519   -.0198008
       aged3 |   -.036798   .0021307   -17.27   0.000    -.0409741   -.0326218
       aged4 |  -.0448259   .0022329   -20.08   0.000    -.0492024   -.0404495
       aged5 |  -.0493361   .0028318   -17.42   0.000    -.0548863   -.0437858
       aged6 |  -.0571131   .0036176   -15.79   0.000    -.0642035   -.0500227
       aged7 |  -.0594136   .0043158   -13.77   0.000    -.0678725   -.0509546
       aged8 |  -.0656497   .0072591    -9.04   0.000    -.0798776   -.0514219
       aged9 |  -.0628879   .0063583    -9.89   0.000    -.0753501   -.0504256
       _cons |   .0233128   .0010467    22.27   0.000     .0212613    .0253643
------------------------------------------------------------------------------
(est5 stored)

Linear regression, absorbing indicators         Number of obs     =  3,741,140
                                                F(   8,  72493)   =       1.94
                                                Prob > F          =     0.0494
                                                R-squared         =     0.6913
                                                Adj R-squared     =     0.3780
                                                Root MSE          =     0.5364

                                 (Std. Err. adjusted for 72,494 clusters in i)
------------------------------------------------------------------------------
             |               Robust
res_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged2 |  -.0015001   .0015554    -0.96   0.335    -.0045486    .0015484
       aged3 |  -.0064596   .0026521    -2.44   0.015    -.0116578   -.0012614
       aged4 |  -.0083613   .0025755    -3.25   0.001    -.0134093   -.0033133
       aged5 |  -.0094254   .0033466    -2.82   0.005    -.0159847   -.0028661
       aged6 |  -.0135198   .0041865    -3.23   0.001    -.0217253   -.0053143
       aged7 |  -.0137764   .0053693    -2.57   0.010    -.0243002   -.0032525
       aged8 |   -.015279   .0089459    -1.71   0.088    -.0328129    .0022549
       aged9 |  -.0120121   .0077225    -1.56   0.120    -.0271481    .0031239
       _cons |   .0101643   .0008789    11.57   0.000     .0084416    .0118869
-------------+----------------------------------------------------------------
         ijk |   absorbed                                 (1884495 categories)
(est6 stored)

Linear regression                               Number of obs     =  1,524,261
                                                F(8, 41375)       =      89.88
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0051
                                                Root MSE          =      .6174

                                 (Std. Err. adjusted for 41,376 clusters in i)
------------------------------------------------------------------------------
             |               Robust
res_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0129155   .0017585    -7.34   0.000    -.0163622   -.0094688
       aged4 |  -.0189207   .0017853   -10.60   0.000      -.02242   -.0154214
       aged5 |  -.0226886   .0024245    -9.36   0.000    -.0274408   -.0179364
       aged6 |  -.0292271   .0031427    -9.30   0.000    -.0353869   -.0230673
       aged7 |  -.0304964   .0040835    -7.47   0.000       -.0385   -.0224927
       aged8 |  -.0370223   .0072882    -5.08   0.000    -.0513073   -.0227373
       aged9 |  -.0323926   .0065004    -4.98   0.000    -.0451335   -.0196517
     size_l1 |  -.0149985   .0006253   -23.99   0.000    -.0162241   -.0137729
       _cons |  -.0736923   .0030195   -24.41   0.000    -.0796107    -.067774
------------------------------------------------------------------------------
(est7 stored)

Linear regression, absorbing indicators         Number of obs     =  1,524,261
                                                F(   8,  41375)   =      11.71
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6615
                                                Adj R-squared     =     0.4255
                                                Root MSE          =     0.4692

                                 (Std. Err. adjusted for 41,376 clusters in i)
------------------------------------------------------------------------------
             |               Robust
res_fe_uv_~t |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       aged3 |  -.0026904     .00232    -1.16   0.246    -.0072376    .0018568
       aged4 |  -.0041613   .0020058    -2.07   0.038    -.0080927     -.00023
       aged5 |  -.0054791   .0028265    -1.94   0.053    -.0110191     .000061
       aged6 |  -.0088792   .0034314    -2.59   0.010    -.0156049   -.0021535
       aged7 |    -.00918    .004598    -2.00   0.046    -.0181921   -.0001679
       aged8 |  -.0102921   .0078677    -1.31   0.191    -.0257129    .0051288
       aged9 |  -.0057137    .006646    -0.86   0.390      -.01874    .0073127
     size_l1 |   .0113588   .0012078     9.40   0.000     .0089915    .0137261
       _cons |    .044752   .0063231     7.08   0.000     .0323587    .0571454
-------------+----------------------------------------------------------------
         ijk |   absorbed                                  (626167 categories)
(est8 stored)

--------------------------------------------------------------------------------------------------
                 (1)        (2)        (3)        (4)        (5)        (6)        (7)        (8) 
                est1       est2       est3       est4       est5       est6       est7       est8 
--------------------------------------------------------------------------------------------------
age_ele1       0.085a                          -0.012a                                            
             (0.001)                          (0.001)                                             

aged2                     0.109a     0.025a               -0.022a    -0.002                       
                        (0.002)    (0.003)               (0.001)    (0.002)                       

aged3                     0.229a     0.067a               -0.037a    -0.006b    -0.013a    -0.003 
                        (0.004)    (0.005)               (0.002)    (0.003)    (0.002)    (0.002) 

aged4                     0.312a     0.087a               -0.045a    -0.008a    -0.019a    -0.004b
                        (0.004)    (0.006)               (0.002)    (0.003)    (0.002)    (0.002) 

aged5                     0.364a     0.089a               -0.049a    -0.009a    -0.023a    -0.005c
                        (0.005)    (0.007)               (0.003)    (0.003)    (0.002)    (0.003) 

aged6                     0.419a     0.088a               -0.057a    -0.014a    -0.029a    -0.009a
                        (0.007)    (0.009)               (0.004)    (0.004)    (0.003)    (0.003) 

aged7                     0.461a     0.087a               -0.059a    -0.014b    -0.030a    -0.009b
                        (0.009)    (0.012)               (0.004)    (0.005)    (0.004)    (0.005) 

aged8                     0.491a     0.079a               -0.066a    -0.015c    -0.037a    -0.010 
                        (0.011)    (0.014)               (0.007)    (0.009)    (0.007)    (0.008) 

aged9                     0.515a     0.080a               -0.063a    -0.012     -0.032a    -0.006 
                        (0.016)    (0.019)               (0.006)    (0.008)    (0.007)    (0.007) 

size_l1                                                                         -0.015a     0.011a
                                                                               (0.001)    (0.001) 
--------------------------------------------------------------------------------------------------
N            3741140    3741140    3741140    3741140    3741140    3741140    1524261    1524261 
R-sq           0.012      0.012      0.710      0.001      0.001      0.691      0.005      0.662 
--------------------------------------------------------------------------------------------------
Standard errors in parentheses
c p<0.1, b p<0.05, a p<0.01

{
\def\sym#1{\ifmmode^{#1}\else\(^{#1}\)\fi}
\begin{tabular}{l*{8}{c}}
\hline\hline
                    &\multicolumn{1}{c}{(1)}&\multicolumn{1}{c}{(2)}&\multicolumn{1}{c}{(3)}&\multicolumn{1}{c}{(4)}&\multicolumn{1}{c}{(5)}&\multicolumn{1}{c}{(6)}&\multicolumn{1}{c}{(7)}&\multicolumn{1}{c}{(8)}\\
                    &\multicolumn{1}{c}{est1}&\multicolumn{1}{c}{est2}&\multicolumn{1}{c}{est3}&\multicolumn{1}{c}{est4}&\multicolumn{1}{c}{est5}&\multicolumn{1}{c}{est6}&\multicolumn{1}{c}{est7}&\multicolumn{1}{c}{est8}\\
\hline
Age$ \_{ijkt}$       &       0.085{$^a$}&                  &                  &      -0.012{$^a$}&                  &                  &                  &                  \\
                    &     (0.001)      &                  &                  &     (0.001)      &                  &                  &                  &                  \\
[1em]
Age$ \_{ijkt}=2$     &                  &       0.109{$^a$}&       0.025{$^a$}&                  &      -0.022{$^a$}&      -0.002      &                  &                  \\
                    &                  &     (0.002)      &     (0.003)      &                  &     (0.001)      &     (0.002)      &                  &                  \\
[1em]
Age$ \_{ijkt}=3$     &                  &       0.229{$^a$}&       0.067{$^a$}&                  &      -0.037{$^a$}&      -0.006{$^b$}&      -0.013{$^a$}&      -0.003      \\
                    &                  &     (0.004)      &     (0.005)      &                  &     (0.002)      &     (0.003)      &     (0.002)      &     (0.002)      \\
[1em]
Age$ \_{ijkt}=4$     &                  &       0.312{$^a$}&       0.087{$^a$}&                  &      -0.045{$^a$}&      -0.008{$^a$}&      -0.019{$^a$}&      -0.004{$^b$}\\
                    &                  &     (0.004)      &     (0.006)      &                  &     (0.002)      &     (0.003)      &     (0.002)      &     (0.002)      \\
[1em]
Age$ \_{ijkt}=5$     &                  &       0.364{$^a$}&       0.089{$^a$}&                  &      -0.049{$^a$}&      -0.009{$^a$}&      -0.023{$^a$}&      -0.005{$^c$}\\
                    &                  &     (0.005)      &     (0.007)      &                  &     (0.003)      &     (0.003)      &     (0.002)      &     (0.003)      \\
[1em]
Age$ \_{ijkt}=6$     &                  &       0.419{$^a$}&       0.088{$^a$}&                  &      -0.057{$^a$}&      -0.014{$^a$}&      -0.029{$^a$}&      -0.009{$^a$}\\
                    &                  &     (0.007)      &     (0.009)      &                  &     (0.004)      &     (0.004)      &     (0.003)      &     (0.003)      \\
[1em]
Age$ \_{ijkt}=7$     &                  &       0.461{$^a$}&       0.087{$^a$}&                  &      -0.059{$^a$}&      -0.014{$^b$}&      -0.030{$^a$}&      -0.009{$^b$}\\
                    &                  &     (0.009)      &     (0.012)      &                  &     (0.004)      &     (0.005)      &     (0.004)      &     (0.005)      \\
[1em]
Age$ \_{ijkt}=8$     &                  &       0.491{$^a$}&       0.079{$^a$}&                  &      -0.066{$^a$}&      -0.015{$^c$}&      -0.037{$^a$}&      -0.010      \\
                    &                  &     (0.011)      &     (0.014)      &                  &     (0.007)      &     (0.009)      &     (0.007)      &     (0.008)      \\
[1em]
Age$ \_{ijkt}=9$     &                  &       0.515{$^a$}&       0.080{$^a$}&                  &      -0.063{$^a$}&      -0.012      &      -0.032{$^a$}&      -0.006      \\
                    &                  &     (0.016)      &     (0.019)      &                  &     (0.006)      &     (0.008)      &     (0.007)      &     (0.007)      \\
[1em]
size\_l1             &                  &                  &                  &                  &                  &                  &      -0.015{$^a$}&       0.011{$^a$}\\
                    &                  &                  &                  &                  &                  &                  &     (0.001)      &     (0.001)      \\
\hline
Observations        &     3741140      &     3741140      &     3741140      &     3741140      &     3741140      &     3741140      &     1524261      &     1524261      \\
\(R^{2}\)           &       0.012      &       0.012      &       0.710      &       0.001      &       0.001      &       0.691      &       0.005      &       0.662      \\
\hline\hline
\multicolumn{9}{l}{\footnotesize Standard errors in parentheses}\\
\multicolumn{9}{l}{\footnotesize {$^c$} p<0.1, {$^b$} p<0.05, {$^a$} p<0.01}\\
\end{tabular}
}

. 
. 
. log close
      name:  <unnamed>
       log:  D:\Vicard\VV\re\inprogress\BRV\results\prediction1_reconstr_fe.log
  log type:  text
 closed on:  29 Sep 2017, 23:41:11
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
